This course's central goal is to introduce the student to the analysis and employment of spatial datasets in the social sciences realm. It begins with a thorough description of R's tools and methods to manipulate and visualize geographic data. After becoming acquainted with the construction of spatial variables, the student learns how economists exploit the latter to uncover the causal mechanisms determining the link between historical developments (e.g., the colonization of America) and today's regional development levels. The course also deepens into various statistical models that incorporate parameters governing a given phenomenon's spatial diffusion, thereby tackling questions such as: how intense is the dissemination of violence across space following the outbreak of civil conflict? Will one municipalities' improvements in educational levels spill to adjacent localities? A discussion on estimation techniques, hypothesis testing, and an introduction to Machine Learning methods for spatial data marks the course's end.
SU Credits : 3
ECTS Credit : 6
Prerequisite : Undergraduate level ECON 301 Minimum Grade of D
Corequisite : -